Job Description
Are you ready to engineer the intelligence that will define the technological landscape of 2026? At Apex Future Systems, we aren't just building software; we are architecting the future of human-machine interaction.
We are seeking a visionary Senior Generative AI Engineer to lead the development of our proprietary Large Language Model (LLM) ecosystem. In this pivotal role, you will bridge the gap between cutting-edge research and production-scale deployment, ensuring our solutions are not only powerful but ethical, scalable, and transformative.
Join a world-class team pushing the boundaries of what's possible in 2026 and beyond.
Responsibilities
- Model Architecture & Development: Design, train, and fine-tune large-scale generative models using state-of-the-art frameworks like PyTorch and TensorFlow.
- RAG Pipeline Optimization: Build and optimize Retrieval-Augmented Generation pipelines to ensure accuracy and reduce hallucinations in real-world applications.
- Deployment & MLOps: Implement scalable MLOps pipelines using Kubernetes and Docker to manage model lifecycle, versioning, and A/B testing.
- Agent Orchestration: Develop autonomous AI agents capable of complex reasoning and multi-step task execution for enterprise clients.
- Ethical AI Governance: Establish and enforce guidelines for AI safety, bias mitigation, and data privacy compliance.
- Technical Leadership: Mentor junior engineers and collaborate with product managers to translate business requirements into technical specifications.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Core Expertise: Deep understanding of NLP, Transformer architectures, and Generative AI principles.
- Programming: Proficiency in Python with extensive experience in C++ for high-performance computing tasks.
- Tools: Experience with Hugging Face, LangChain, vector databases (Pinecone, Weaviate), and cloud platforms (AWS, GCP).
- Experience: Minimum of 5 years of experience in AI/ML engineering, with a focus on LLMs.
- Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.